Milan Sonka

University of Iowa — United States

Computer Science · Physical Sciences

75h-index33.7kcitations672works3.52yr avg
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Research Topics

Medical Image Segmentation Techniques(166), Retinal Imaging and Analysis(138), Coronary Interventions and Diagnostics(109), Radiomics and Machine Learning in Medical Imaging(88), Cardiac Imaging and Diagnostics(85)

Publications672 total

Agricultural Injury Severity Prediction Using Integrated Data-Driven Analysis: Global Versus Local Explainability Using SHAP
Safety·2026Open Access
Latent diffusion for medical image segmentation: End-to-end learning for fast sampling and accuracy
Biomedical Signal Processing and Control·2025
Agricultural Injury Severity Prediction Using Integrated Data-Driven Analysis: Global Versus Local Explainability Using SHAP
2025Open Access
Fully automated IVUS image segmentation with efficient deep-learning-assisted annotation
Computers in Biology and Medicine·2025Open Access
Comparative Evaluation of Deep Learning Models for 3D Segmentation and Volumetry of Vestibular Schwannomas Using Large Heterogeneous Datasets with External Validation
American Journal of Neuroradiology·2025Open Access
Loss of Enhancement in Vestibular Schwannomas Post Stereotactic Radiosurgery: Impact on Tumor Control and Serviceable Hearing
Otology & Neurotology·2025
Risk Stratification and Coronary Optical Coherence Tomography Findings in Asymptomatic Patients With Type 1 Diabetes Mellitus
Physiological Research·2025Open Access
Impact of evolocumab on coronary physiology and microstructure in de-novo heart transplant recipients
The Journal of Heart and Lung Transplantation·2025Open Access
The hope and the hype of artificial intelligence for syncope management
European Heart Journal - Digital Health·2025· 1 citedOpen Access
Spectral U-Net: Enhancing Medical Image Segmentation via Spectral Decomposition
2025· 3 cited
U-Net V2: Rethinking the Skip Connections of U-Net for Medical Image Segmentation
2025· 63 cited
Sli2Vol+: Segmenting 3D Medical Images Based on an Object Estimation Guided Correspondence Flow Network*
2025· 4 citedOpen Access
Asymmetry Is the Norm in “Cloverleaf” Aortic Root Structure
2025Open Access
Predicting admission for fall‐related injuries in older adults using artificial intelligence: A proof‐of‐concept study
Geriatrics and gerontology international/Geriatrics & gerontology international·2025· 2 citedOpen Access
Sli2Vol+: Segmenting 3D Medical Images Based on an Object Estimation Guided Correspondence Flow Network
arXiv (Cornell University)·2024Open Access
NIMG-40. RADIOMICS-BASED DIFFERENTIATION OF GLIOBLASTOMA AND METASTATIC DISEASE: DOES DIFFERENCE IN TYPE OF T1-CONTRAST ENHANCED SEQUENCE MATTER?
Neuro-Oncology·2024Open Access
Group Vision Transformer
2024
Contrastive Generative Self-Supervised Learning for 3D Medical Image Segmentation
2024Open Access
Spectral U-Net: Enhancing Medical Image Segmentation via Spectral Decomposition
arXiv (Cornell University)·2024Open Access
Radiomics-Based Differentiation of Glioblastoma and Metastatic Disease: Impact of Different T1-Contrast-Enhanced Sequences on Radiomics Features and Model Performance
American Journal of Neuroradiology·2024· 2 citedOpen Access
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Frequent Co-authors

Michael D. Abràmoff(16), Mona K. Garvin(11), Eric A. Hoffman(10), Hille W. van Dijk(6), Reinier O. Schlingemann(6), Frank D. Verbraak(6), Geoffrey McLennan(6), Pauline H. B. Kok(5), J. Hans DeVries(5), Andreas Wahle(5), Kyungmoo Lee(5), Juerg Tschirren(4), Meindert Niemeijer(4), Mirjam E. J. van Velthoven(3), Renuka Uppaluri(3), Susan Mitchell(3), Boudewijn P. F. Lelieveldt(3), Xiangmin Zhang(3), Michael F. Insana(3), Kálmán Palágyi(3)